Intelligent thermostat control system

ABSTRACT

An intelligent thermostat control system for a building, such as a residential home, that automatically adjusts a thermostat setting in the home based on real-time data continually received from mobile devices and/or social media files associated with the residents. This allows the thermostat controller to override the explicit programmed settings with implicit settings based on activity analysis taking the actual locations and schedules of the residents into account. The intelligent thermostat controller may control different zones differently to take into account the schedules and locations of specific residents associated with specific zones. The temperature controller may also adaptively learn a number of parameters based on monitored data, such as travel times and heating/cooling times for the zones based, to determine times for adjusting the thermostats.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is a continuation application of U.S. patentapplication Ser. No. 14/103,270 filed on Dec. 11, 2013 and U.S. patentapplication Ser. No. 15/068,921 filed on Mar. 14, 2016. The entirecontents of U.S. patent application Ser. No. 14/103,270 and U.S. patentapplication Ser. No. 15/068,921 are incorporated herein by reference.

TECHNICAL FIELD

The present invention relates to thermostats for buildings and, moreparticularly, to intelligent thermostat controllers.

BACKGROUND

Many homes have programmable thermostats that allow a user to entermultiple settings for running the heat, ventilation and air conditioning(HVAC) systems to match the expected occupancy patterns of the residentsto save energy. Most homes also have multiple zones with dedicated HVACunits, each having a separate programmable thermostat. It is generallyappropriate to heat or cool different zones on different schedules tosave energy. In some homes, for example, it may be appropriate to heatand cool the main living zone during waking hours, while the bedroomzone can be heated and cooled during sleeping hours. It may also beadvantageous to turn the thermostats well down (i.e., turn the heatingtemperature setting up and the air conditioning temperature down)whenever the residents are scheduled to be away from home for extendedperiods, for example during weekday working hours. The thermostats canbe programmed to automatically adjust to more comfortable settings whenthe residents are scheduled to return home. There may also be specialevents, such as vacations, when the entire family is away from home forextended periods. When the entire family is away from the home, energycan be saved by turning the thermostats well down for the duration oftheir absence.

In general, more accurate thermostat programming reflecting the actualoccupancy of the residents can save energy, but few homeowners rememberto adjust the thermostat as frequently as schedules change. And even ifa homeowner were to endeavor to set the thermostats daily to reflect theexpected occupancy schedules of the residents, the thermostat settingsmight still turn out to be less then optimal, at least on someoccasions, due to unexpected changes in the schedules.

SUMMARY

According to one embodiment of the present invention, a thermostatcontrol system is provided. The thermostat control system includes athermostat controller receptive of first location and scheduleinformation and operative to adjust at least one thermostat within abuilding. The thermostat controller accesses second location andschedule information of a social media file associated with a residentof the building if the first location and schedule information are notreceived periodically, adaptively learns a predicted heating/coolingtime for the building, adjusts the thermostat based on the adaptivelylearned heating/cooling time, on the first location and scheduleinformation and on the second location and schedule information andrecords historical data files for explicit thermostat setting datarelated to preprogrammed settings entered into the thermostat andimplicit thermostat setting data determined from analyses of userslocations and schedules, direct thermostat setting data, first locationand schedule data, second location and schedule data and resident andzone occupancy data.

According to one aspect of an embodiment invention, the intelligentthermostat controller receives location and/or schedule information formultiple residents of the building. Different residents may beassociated with different zones that each have separate thermostatsettings. The thermostat controller performs the activity analysis formultiple residents and multiple zones to determine the implicitthermostat settings for the different zones and adjusts the thermostatsettings for the zones accordingly.

According to another aspect of an embodiment invention, the intelligentthermostat controller adaptively learns parameters, such as travel timesand heating/cooling times for the zones of the building, based onmonitored data received over time. The timing for adjusting to theimplicit thermostat settings is then set based on the location and/orschedule data for the residents together with the learned parameters.

Additional features and advantages are realized through the techniquesof the present invention. Other embodiments and aspects of the inventionare described in detail herein and are considered a part of the claimedinvention. For a better understanding of the invention with theadvantages and the features, refer to the description and to thedrawings accompanying figures.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

The subject matter which is regarded as the invention is particularlypointed out and distinctly claimed in the claims at the conclusion ofthe specification. The forgoing and other features, and advantages ofthe invention are apparent from the following detailed description takenin conjunction with the accompanying drawings in which:

FIG. 1 is a block diagram for an intelligent thermostat control system.

FIG. 2 is a block diagram for a thermostat controller for theintelligent thermostat control system.

FIG. 3 is a logic flow diagram for a computer-implemented routine foroperating the thermostat controller for the intelligent thermostatcontrol system.

DETAILED DESCRIPTION

Embodiments of the present invention may be realized in an intelligentthermostat control system for a building, which is described as aresidential home in the examples described below. The home may havemultiple residents and multiple independently controlled heating,ventilation and air conditioning (HVAC) zones with separate programmablethermostats. Although many homes have multiple zones, embodiments of theinvention may be applied to single zone HVAC systems if desired. Inaddition, while the embodiments described below are directed to aresidential home, the same principles may be applied to commercial,industrial and any other temperature controlled location.

With reference now to FIG. 1, an intelligent thermostat control system10 includes a thermostat controller 24 forming part of the customerpremises equipment 20A in a building. In this example, the building is aresidential home that serves to represent one of many homes and otherbuildings that may have similar customer premises equipment 20A-20N. Thethermostat controller may be configured with “contact profiles”containing network and contact information for downloading the locationand schedule information for each resident. In general, sources oflocation and schedule information include mobile units (e.g., cellulartelephones, tablets, etc.) and social media files (e.g., Facebook®,Twitter®, LinkedIn®, etc.) associated with the residents. In thisparticular example, the thermostat controller 24 utilizes the Internet12 to functionally connect with online social media files 14A-14Nassociated with the residents of the home.

A social media “location tracking” option typically allows a user'ssocial media file to track the location of the associated resident'smobile unit, which allows location data as well as schedule data to beobtained from the social media file. Alternatively or in addition, thethermostat controller 24 may utilize a mobile data network 16 to connectdirectly with the mobile units 30A-30N associated with multipleresidents of the home. The mobile units typically maintain location datafor the unit and may also maintain schedule data, such as calendars andalarms. Some users may prefer to keep their schedule in their mobileunit rather than a social media file. For these users, the thermostatcontroller 24 utilizes a mobile data network 16 to communicate directlywith the user's mobile unit.

The customer premises equipment 20A includes the thermostats 22 for oneor more HVAC zones and the thermostat controller 24, which may beconnected to a local home-area network 26. The thermostat controller 24intelligently adjusts the programmed settings of the thermostats 22based on monitored schedule and location data for multiple residentsobtained from the mobile devices and social media files associated withthe residents. To do so, the thermostat controller 24 communicates overone or more networks, such as the Internet 12 and the wireless datanetwork 16, with online social media files 14A-14N and mobile units30A-30N associated with the residents. In some cases, the social mediafiles 14A-14N may include location and schedule information for theresidents entered by the residents or communicated from the mobile unitsto the social media files. In other cases, the mobile units may be thebest resource for obtaining the schedule and location data. Depending onthe preference of the specific users, the thermostat controller 24 mayaccess location and schedule information from mobile units, social mediafiles, or both, as appropriate for different users. The thermostatcontroller 24 may also access these resources in a priority order. Forexample, the thermostat controller may be configured to receive dataperiodically from a user's mobile unit, and resort to accessing theuser's social media whenever the mobile unit does not report at theexpected intervals.

Referring to the mobile unit 30A to provide an illustrative example,alternatively or in addition to accessing a resident's social mediafiles, the temperature controller 24 may directly access the resident'smobile unit. To facilitate this connectivity, this mobile unit includesa thermostat control application or “app” 32 configured to autonomouslycommunicate with the thermostat controller 24. The app periodicallyreports location and schedule data to keep the thermostat controller 24apprised of the current location and schedule information maintained onthe mobile unit. The mobile unit typically includes programs withschedule information, such as a calendar, alarm, or a mail program withscheduling functionality. The mobile unit may also include a socialmedia interface 36 that provides location information, scheduleinformation or both to the resident's social media file.

FIG. 2 is a block diagram of an example thermostat controller 24, whichtypically includes a mobile unit interface 40 configured to communicatevia a mobile data network with the thermostat control app 32 on eachresident's mobile unit. The mobile data interface may implement a “pull”model in which the mobile unit interface 40 requests data downloads fromthe app according to a schedule set by the mobile unit interface.Alternatively, the mobile data interface for the thermostat controller24 may implement a “push” model in which the app automatically sendsdata according to a schedule set by the app. The push model may beadvantageous, for example, by allowing the mobile unit to initiate orincrease the frequency of data updates when the underlying schedule orlocation data experiences a change. For example, a schedule or alarmchange may cause a data update, and the frequency of data updates mayincrease when the location of the mobile unit is changing. The pushmodel may also reduce the frequency of data updates in response to lowbattery and low signal strength conditions at the mobile unit. In eithercase, the mobile unit interface 40 at the thermostat controller 24continually receives schedule and location updates from the thermostatcontrol app running on the mobile unit 32.

The thermostat controller 24 may also include an online social mediainterface 41 that communicates via the Internet with each resident'sonline social media file 14. This may provide a backup, or in some casesa less expensive communication interface, for users who maintainschedule and location data in their social media files. A thermostatinterface 42 controls the thermostat 22, which may represent multiplethermostats controlling separate thermostats for different zones in thebuilding. Although any type of connection may be utilized, a wirelessbridge may be suitable for connecting the thermostat interface 42 withthe thermostat 22. A local network interface 43 may also be provided tointegrate the thermostat controller with a home area network or otherlocal network present in the building, which may provide connectivity tothe thermostat 22.

The thermostat controller 24 also includes a user interface 44, whichmay typically be accessed from a laptop computer, mobile device or otherremote computer allowing a user to conveniently program and obtaininformation from the thermostat controller. For example, the userinterface 44 may be used to create and activate explicit settingprofiles for programming the thermostats in the building, associateparticular residents with specific zones, and create mobile unit andsocial media contact information profiles for the residents. The userinterface 44 may also be used to set various parameters utilized by thethermostat controller, such as thermostat setting parameters and networkinterface parameters. It may also be used to activate mobile devices foruse with the system, activate social media files for use with thesystem, and so forth.

A variety of parameters may be provided for administrative control by anauthorized user, such as maximum heating temperatures, minimum coolingtemperatures, override and interrupt hold periods, contact informationfor sending alerts to a system administrator, network interfaceparameters, parameters used in activity analysis, and the like. Thethermostat controller may also record and create historical data filesfor a variety of parameters, such as explicit thermostat setting data,implicit thermostat setting data, direct thermostat setting data,resident location data, resident schedule data, resident occupancy data,zone occupancy data, mobile device information reporting data, socialmedia information reporting data, and so forth.

The thermostat controller 24 also includes an activity analysis feature45, which determines when to replace the explicit thermostat settingswith implicit settings based on mobile unit locations, schedule data,travel patterns, predicted travel times, and predicted heating/coolingtimes required to bring HVAC zones to desired temperatures. Thethermostat controller 24 may utilize ambient and building temperatures46 to predict the heating/cooling times required to bring HVAC zones todesired temperatures. Activity analysis may also adjust the thermostatsettings based on location data, schedule data, or a combination oflocation and schedule data. In particular, activity analysis may uselocation data, schedule data, and learned parameters such as predictedtravel times and temperature response data for the HVAC zones to adjustthe thermostat settings sufficiently in advance of the projected arrivalof the resident so that the appropriate zone temperatures have reachedcomfortable settings when the resident arrives at the home.

While many thermostat adjustment triggers may be defined, thecombination of a resident's schedule indicating that a scheduledactivity has ended together with location information indicating thatthe resident is traveling in a manner consistent with returning homewill ordinarily trigger heating or cooling one or more zones of theresidence in time for their return. For example, the activity analysismy prevent a thermostat from adjusting from an energy saving setting toa comfortable setting when the activity analysis determines that theresident is at a restaurant located 30 minutes away from the home. Oncethe activity analysis determines that the resident is headed home, thethermostat may be adjusted to the comfortable setting about 15 minutesbefore the resident arrived. An unscheduled return to the residence mayalso trigger heating or cooling the residence as a resident approachesor arrives at the residence. Learned parameters regarding residentactivity, travel times, and zone heating/cooling response may also befactored into the timing of the adjustments to the implicit thermostatsettings.

The activities analysis feature 45 may work in conjunction with acentral management feature 47, which keeps track of the explicitthermostat settings for the various zones and combines the activityanalyses for multiple residents to determine implicit settings for thethermostats in the various zones. Centralized management allows thetemperature controller to take into account the activity analyses formultiple residents and the association of different residents withdifferent HVAC zones in the residence. Over time, the activitiesanalysis and central management features may adapt to reflect learnedparameters gained by monitoring the schedules, travel times andheating/cooling response of the various zones in the building over time.The system may also adapt to learned behaviors of the residents, such asrecurring travel and activity patterns not reflected in the configuredschedule data. This allows the activity analysis and central managementfeatures to adapt the thermostat control procedures to learnedparameters in an ongoing process to proactively adjust the thermostatsettings to provide comfortable living conditions while minimizingenergy usage.

Of courts, the activity of the residents will sometimes varyunpredictably from their planned schedules, residents may forget ormisplace their mobile units, residents may not program all of theirplanned activities into their mobile units or social media files, andother events may occur that unexpectedly vary the occupancy pattern ofthe residence. To account for these types of situations, the thermostatcontroller allows interrupt settings, such as those entered directlyinto a thermostat, to override the explicit (preprogramed) settings aswell as the implicit settings determined by the thermostat controllerthrough activities analysis. The thermostat controller thereforeoperates according to predefined explicit settings (i.e., theconventional programmed settings entered into the programmablethermostat) that can be overridden by implicit settings determinedthrough activity analysis for the residents based on the location andschedule information received from their mobile devices and socialmedia. The explicit settings as well as the implicit may also beoverridden by interrupt settings directly entered into the thermostats.In this manner, the intelligent thermostat controllers more efficientlymeet the needs of the residents by automatically adjusting thermostatsettings based on monitored locations, activities, and schedules of theresidents, while still allowing the residents to interrupt theprogramming through manual thermostat adjustment when needed.

FIG. 3 is a logic flow diagram for an example routine 60 for operatingthe thermostat controller 24 for a representative thermostat. It will beunderstood that multiple thermostats may be controlled in a similarmanner for multiple HVAC zones in the building. In block 62, thecontroller initially sets the thermostat to the explicit setting ormaintains the current setting in the absence of a determination to alteror override the current setting. In the absence of an interrupt at block67, the routine advances to block 63, where the controller gathersrelevant data, typically including information obtained from the userinterface (e.g., explicit thermostat settings that may change from timeto time), information obtained from the mobile units (e.g., locationinformation for the residents), and information obtained from socialmedia (e.g., scheduled activity data for the residents). The routine 60proceeds from block 63 to decision block 64, in which the controllerdetermines whether the gathered information indicates that a thermostatchange may be indicated. For example, the gathered data may indicatethat one of the residents has varied from a predefined schedule or istraveling toward the residence. If the gathered data does not indicate apotential thermostat change, the “no” branch is followed from decisionblock 64 to block 62, in which the thermostat maintains the currentthermostat setting, which may be an explicit setting, an implicitsetting or an interrupt setting.

If the gathered data indicates a potential thermostat change, the “yes”branch is followed from decision block 64 to block 65, in which thethermostat controller runs the activity analysis to determine a desiredthermostat setting typically based on location and schedule data for oneor more residents. When determining the desired thermostat setting, thethermostat controller may take into account the explicit setting presetfor the thermostat as well as implicit settings determined for multipleresidents based on activity analysis. For example, the activity analysisfor each resident may include their current location, their recentlocations (e.g., whether they are traveling toward the residence), andtheir schedule as determined from their location and schedule data. Thetemperature controller may also consider learned parameters, such astravel times from various locations and heating/cooling times for thevarious zones of the building based on ambient and building temperaturemeasurements. The routine 60 then proceeds from block 65 to block 66, inwhich the thermostat controller sets the thermostat to the determinedsetting typically via a wireless bridge between the thermostatcontroller and the thermostat.

An interrupt reflecting a directly entered thermostat setting may bereceived at any time, as indicated by decision block 67 which followsboth block 62 and block 66. An interrupt indicates that a user has takenan affirmative step to directly set the temperature, for example bymanually adjusting a thermostat to a desired temperature. If aninterrupt has been received, the “yes” branch is followed from decisionblock 67 to block 68, in which the temperature controller sets thethermostat to the direct setting, which may also use the wireless bridgebetween the thermostat controller and the thermostat. The routine 60then proceeds from block 68 to block 69, in which the temperaturecontroller waits for a preset hold period, which may be a userconfigurable parameter. After waiting the prescribed time, the routine60 returns to block 63, in which the temperature controller gathersrelevant data. On the other hand, if an interrupt has not been receivedat decision block 67, the “no” branch is followed back to block 63, inwhich the temperature controller gathers relevant data, and the routinecontinues as previously described.

While conventional programmable thermostats are typically capable ofbeing programmed on any desired frequency, most people program theirthermostats once or at most occasionally. A typical homeowner mayinitially program the thermostat with seasonal settings based onexpected occupancy of the residence and then fail to make any furtheradjustments as schedules change. As a result, the thermostat programsare often set without attempting to follow the daily schedules of theresidents as those schedules vary over time. And even if the residentswere to program thermostat on a daily basis, their actual scheduleswould often vary from their expected schedules. At present, there is noconvenient way for a homeowner to reprogram the thermostat as scheduleschange. Conventional programmable thermostats also lack the ability totake into account varying scheduled for multiple residents, some of whommay be associated with specific zones, when establishing the thermostatsettings.

The intelligent thermostat controller solves this problem byautomatically adjusting the thermostat setting based on real-time datacontinually received from mobile devices and social media filesassociated with the residents. This allows the thermostat controller tooverride the explicit programmed settings with implicit settings basedon activity analysis taking the actual locations and schedules of theresidents into account. The real-time location and schedule data may beobtained over the Internet or via a mobile data network from theresidents' mobile devices and social media files. The intelligentthermostat controller may also control different zones differently totake into account the schedules and locations of specific usersassociated with specific zones. For example, the thermostat setting foran apartment zone may be adjusted when a person associated with thatzone is determined to be present or in the process of returning to thehome. As another example, the thermostat controller for a home office orworkshop zone may be adjusted when a specific person associated withthat zone is determined to be present or in the process of returning tothe home. It will be appreciated, of course, that many differentthermostat control schemes may be defined by individual users based onthe needs of their households, which will vary from household tohousehold.

While mobile devices (e.g., cellular telephones) are described as thelocation determining devices carried by the relevant persons, othertypes of location or presence determining devices may utilized. Forexample, the intelligent thermostat control system may work with RFIDidentification cards, entry control systems, position reporting devices,cameras, automatic lighting systems, infrared sensors or other type ofsystems for detecting the presence of persons within the building. Thesystem may also use additional types of inputs to implement thermostatoverrides, for example automatically adjusting the thermostat whenever aspecific light switch or other piece of equipment is turned or off. Theembodiments described above provide simple examples to illustrate theprinciples of the innovation and many other options, alternatives andlevels of sophistication will become apparent to those skilled in theart once the basic principles of the innovation have been ascertainedbased on the specific examples provided.

As an option, the intelligent thermostat control system may beimplemented as part of a home area network, which may provideconnectivity to the thermostats. Whether deployed independently or aspart of a larger computer network, the thermostat control system may beconfigured to intelligently control the thermostat settings for multiplezones of the home based on real-time data indicating the locations orschedules for multiple residents of the home. The intelligent thermostatcontroller may control different zones differently to take into accountthe occupancy of specific residents associated with specific zones. Thethermostat controller may utilize schedule data, location data, or bothfor each resident. The location and/or schedule data may be receivedfrom the resident's mobile unit, social media file, or both as desired.The real-time location and schedule data may be obtained over theInternet and/or via a mobile data network.

In addition, the temperature controller may adaptively learn a number ofparameters based on monitored data, such as travel times based onlocations and schedule information for the residents, andheating/cooling times for the zones based on ambient and building zonetemperatures. For example, the activity analysis may determine predictedtravel times from mobile unit locations to the home based on thelocation, time of day and day of the week. The temperature controllermay also adaptively learn activity and travel patterns for theresidents. These adaptively learned parameters are then used todetermine the times for adjusting the thermostats to the implicitsettings. This allows the thermostats to be set to the implicit settingssufficiently in advance to allow the zones to reach the desiredtemperatures in time for the arrival of the residents.

To provide one simple example to illustrate the basic functionality, animplicit setting based on activity analysis may override a predefinedexplicit thermostat setting by preventing a change in the temperaturesetting until the activity analysis determines based on locationinformation or schedule information (or both) that one of the residentsis likely on their way home. Similarly, an implicit setting may overridean explicit predefined setting by adjusting the thermostat setting to acomfortable setting when the location information indicates that aresident is enroute home. To continue this example, the person'sschedule may impact the activity analysis when the person leaves theresidence. For example, if that person is scheduled to be at anotherplace, the thermostat may be immediately adjusted to an energy savingsetting as soon as they leave the premises. But if that person isscheduled to be home, the temperature controller may maintain thetemperature setting at a comfortable setting for a longer period,effectively anticipating that they will return home shortly. Adaptiveprogramming allows the activities analysis to learn behavior patternsbased on the combination of location and schedule data over time,allowing for more effective thermostat control as the behavior patternsof the residents are learned over time.

Activity analysis may also be performed, and combined as appropriate,for multiple residents who may be associated with different zones.Schedule data may also be combined with location data, for example topredict that a resident in transit is not headed home, but is insteadheaded to another appointment. In general, predicted travel times may bebased location data alone, schedule data alone, or a combination oflocation and schedule data, typically depending on which data isavailable for a particular resident. Predicted HVAC zone temperatureresponse times may also be taken into consideration, typically based onambient temperatures, zone temperatures, and learned heating/coolingresponse times to estimate the times required to adjust the zonetemperatures to the desired temperatures. Centralized management allowsthe temperature settings to be adjusted based on the combined needs ofthe various residents, while the adaptive programming can learn groupbehaviors to assist in effective thermostat control.

The intelligent thermostat controller achieves advantages not realizedby prior thermostat controllers by intelligently adjusting thethermostat settings based on real-time monitored data, which may includeboth location and schedule data for the residents. The activities ofmultiple residents may be considered since, for example, it may beappropriate to adjust the thermostat for a common living zone to acomfortable setting whenever any of the residents are home. In addition,the thermostat settings for different zones may be varied based on theparticular residents that are determined to be home at any particulartime. As another example, the thermostat setting in an in-law suite,basement apartment or teenager's room may be controlled on based theactivity analysis for one or more residents assigned to that particularzone. In yet another example, the thermostat setting in a workshop orhome office may be adjusted to a comfortable setting only when aspecific resident authorized to use the workshop or office is determinedto be present. Similar controls may be defined for exercise rooms, artstudios, or other any other special purpose zone within the home.Interrupts for direct thermostat settings may be enabled or disabled forparticular zones, residents, times of day and so forth.

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting of the invention. Asused herein, the singular forms “a”, “an” and “the” are intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. It will be further understood that the terms “comprises”and/or “comprising,” when used in this specification, specify thepresence of stated features, integers, steps, operations, elements,and/or components, but do not preclude the presence or addition of onemore other features, integers, steps, operations, element components,and/or groups thereof.

The corresponding structures, materials, acts, and equivalents of allmeans or step plus function elements in the claims below are intended toinclude any structure, material, or act for performing the function incombination with other claimed elements as specifically claimed. Thedescription of the present invention has been presented for purposes ofillustration and description, but is not intended to be exhaustive orlimited to the invention in the form disclosed. Many modifications andvariations will be apparent to those of ordinary skill in the artwithout departing from the scope and spirit of the invention. Theembodiment was chosen and described in order to best explain theprinciples of the invention and the practical application, and to enableothers of ordinary skill in the art to understand the invention forvarious embodiments with various modifications as are suited to theparticular use contemplated.

The diagrams depicted herein illustrate just one example. There may bemany variations to these diagrams or the steps (or operations) describedtherein without departing from the spirit of the invention. Forinstance, the steps may be performed in a differing order or steps maybe added, deleted or modified. All of these variations are considered apart of the claimed invention.

While the preferred embodiment to the invention had been described, itwill be understood that those skilled in the art, both now and in thefuture, may make various improvements and enhancements which fall withinthe scope of the claims which follow. These claims should be construedto maintain the proper protection for the invention first described.

What is claimed is:
 1. A thermostat control system, comprising: athermostat controller receptive of first location and scheduleinformation from a control application of a mobile unit via a mobiledata network and operative to adjust at least one thermostat within abuilding, wherein the thermostat controller: accesses second locationand schedule information of a social media file, which is different fromthe first location and schedule information, and which is associatedwith a resident of the building if the first location and scheduleinformation are not received periodically, adaptively learns a predictedheating/cooling time for the building, adjusts the thermostat based onthe adaptively learned heating/cooling time, on the first location andschedule information and on the second location and schedule informationof the social media file; and records historical data files for explicitthermostat setting data related to preprogrammed settings entered intothe thermostat and implicit thermostat setting data determined fromanalyses of users locations and schedules, direct thermostat settingdata, first location and schedule data, second location and scheduledata and resident and zone occupancy data.